Papers with retrieval-augmented techniques

1 papers
From One to Many: Expanding the Scope of Toxicity Mitigation in Language Models (2024.findings-acl)

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Challenge: toxicity mitigation in language models has been focused on single-language settings . however, widespread adoption of LLMs has introduced a range of unknown -harms .
Approach: They employ translated data to evaluate and enhance mitigation techniques in the absence of sufficient annotated datasets across languages.
Outcome: The proposed approach compares translation quality and retrieval-augmented mitigation techniques under static and continual toxicity mitigation scenarios.

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